Data and AI be ready for AI with trusted data€¦ · Marketing/Ad budget optimization Loyalty program analytics Shop geolocation optimization Logistics optimization Digital Experience

Data and AIbe ready for AI with trusted data —Arkadiusz WiśniewskiUG&I LeaderIBM AnalyticsCentral & Eastern Europe

Think 2019 / DOC ID / September 19, 2019 / © 2019 IBM Corporation

What organizations really want

2IBM Cloud / © 2019 IBM Corporation

Grow revenue

Mitigate risk

Innovate

Reduce cost

1

2

3

4

2

What organizations really want

IBM Cloud / © 2019 IBM Corporation

POS VISITS

AVERAGE VALUE OF BASKET

PROMO CONVERSION RATE

CAMPAIGN CONVERSION RATE

(NET) CUSTOMER AQUISTION

CHURN

PURCHASE FREQUENCY

SHARE OF WALLET

KNOW YOUR

CUSTOMERS,

PRODUCTS,

INTERACTIONS

REVENUE

INCREASE

MARGIN

INCREASE

COST

OPTIMIZATION

DEMAND FORECASTING

PLANNING & BUDGETING

3

4

AI is a Sciencecomputers performing cognitive functions associated with human minds.

Machine learning, deep learning, neural networks, predictive analytics, prescriptive analytics, etc. are all technologies that enable AI.

IBM Cloud / © 2019 IBM Corporation 4

ARTIFICIAL INTELLIGENCE USE CASES

Customer Intelligence

Customer segmentation

Campaign targeting (outbound)

Next best action recommendation

(outbound/inbound)

Event-based marketing

(batch/real-time)

Credit Scoring

Product Intelligence

Product basket analysis

Weather-based promotions

Product demand forecasting

Stock outoptimization

Customer Service and Operations

Campaign portfolio optimization

Customer survey analytics

Marketing/Ad budget optimization

Loyalty program analytics

Shop geolocation optimization

Logisticsoptimization

Digital Experience and Engagement

Brandmonitoring

Social mediaanalytics

Client opinionmining

Competition and market monitoring

Newsletter and communications personalization

Innovations

Analytics environment modernization assessment

Data FirstWorkshop

Migration to Data Science environment

in the cloud

IBM Cloud / © 2019 IBM Corporation5

80%of data is either

inaccessible, untrusted or unanalyzed

81%do not

understand the data required for

AI

There is no AI without an IA (information architecture)

6

No amount of AI algorithmic sophistication will overcome a lack of data [architecture] … bad data is simply paralyzing.

“IBM Cloud / © 2019 IBM Corporation

Organize Build Deploy Manage

1. What AI teams Want to Focus on

2. Where 40-80% of their time spent on 3. Where organizations see business results

4 critical steps to operationalizing AIBusiness-Ready data




2. Where 40-80% of their time spent on 3. Where organizations see business results

Discover ProfileAssess Quality

CurateIntegrate Catalog Govern





3. Where organizations see business results

Develop Model

Prepare Data

Deploy Model

Explore Data

Manage Model

Retrain Model



2. Where 40-80% of their time spent on

9

COLLECT - Make data simple and accessible

ORGANIZE - Create a business-ready analytics foundation

ANALYZE - Build and scale AI with trust & explainability

INFUSE - Operationalize AI throughout the business

AI

The AI Ladder A prescriptive approach to the journey to AI

Unlock the value of data for an AI in multicloud world

One Platform, Any Cloud

Talent & Skills

IBM Cloud / July 2019 / © 2019 IBM Corporation10

The big from the small. The simple from complex.The structured from …


The IBM analytics portfolio

Write once,

access everywhere

with a common access layer to

foster application independency

Prepare, publish, integrate and

protect

data to obtain better insights and

to avoid regulatory incompliance

Hybrid Data Management

Unified Governance & Integration

Automation through Machine Learning

Collect Organize

Descriptive, predictive,

prescriptive

To understand the now and to

predict the future in order to

influence events

Data Science & Visualization

Analyze

Hybrid Cloud Foundation

Data must be complete,

applicable and accessible

everywhere.

Discover, classify and

understand all types of

data

Data must be secure,

clean and easy to find to

encourage trusted self-

service access.

Understand where data

came from and its quality

Ability to drive self-service

discovery and automate decision

making to evolve the business

Provide a view of all information to

those that need it and allow them

to access it.

Organize - Elements for Success

Know Trust Use

Organize your Data Govern your Data Drive Intelligence from Data

Finding The Data Is Key


A data catalog ensures capabilities that enable any user, from business as well as from IT, to easily discover, understand, associate and consume data that is trusted and meaningful.

A data catalog additionally supports crowdsourcing that allows every user collaborate and contribute their knowledge, as well as benefit from suggestions and completeness.

WHATWHERE

WHO WHEN

One single,

seamless

catalog

experience

that serves

different

personas on

public,

private and

on-prem

All

Governance and

Integration

capabilities

converged

with

Watson

Knowledge

Catalog


14

* Evolving capability** Future roadmap

One Catalog for IT Users & Knowledge Works - Powered by Machine Learning

Automated Data Curation Self-Services Interaction *

Core Governance Services

Policy Management & enforcement *

Auto Analyze Data Quality *

Auto Assign Business Terms *

Business Glossary Management *

Entity & Consent Management *

Auto Discover & Classify Data *

Data Sources

Data Engineer

Business Users

Data Scientist

Data Quality Analyst

Governance Officers

Data Steward

CDO

Systems of Insights

Cloud

Hadoop

Social Media

Unstructured

Other External

IOT

Systems of Record

Users

Logs

Auto Detect Sensitive Data *

Data Lineage *

Basic Data Preparation

Search & Find Relevant Data

Recommendations & Data Insights

Data Archival & DisposalModel Governance & Bias Reporting **

Reference Data Management **

Data Quality & Exception Mgt *

Tagging, Comments Annotation & Share

Data Integration & Replication

Data Integration (DataStage) *

Multi-Cloud Data Integration **

Deployment: OnPrem, Public Clouds (Azure, AWS, IBM, Google) and IBM ICP for Data

Data Stage + Real-Time Replication **

Data Replication *

Unstructured Curation (StoredIQ) *

Advanced Data Preparation **

Industry Models & Accelerators

Knowledge

Catalog

Open Metadata Integration (Egeria)

Metadata Management & Data Catalog

ML Infused Everywhere Embedded Workflow

IBM Unified Governance & Integration Strategy












Data Sources

Data Engineer

Business Users

Data Scientist


Governance Officers

Data Steward

CDO

Systems of Insights

Cloud

Hadoop

Social Media

Unstructured

Other External

IOT

Systems of Record

Users

Logs


Data Lineage *




Data Archival & DisposalModel Governance & Bias

Reporting **Reference Data Management

**Data Quality & Exception

Mgt *







Data Replication *




Knowledge

Catalog
















Data Sources

Data Engineer

Business Users

Data Scientist


Governance Officers

Data Steward

CDO

Systems of Insights

Cloud

Hadoop

Social Media

Unstructured

Other External

IOT

Systems of Record

Users

Logs


Data Lineage *







Mgt *







Data Replication *




Knowledge

Catalog
















Data Sources

Data Engineer

Business Users

Data Scientist


Governance Officers

Data Steward

CDO

Systems of Insights

Cloud

Hadoop

Social Media

Unstructured

Other External

IOT

Systems of Record

Users

Logs


Data Lineage *






**








Data Replication *




Knowledge

Catalog
















Data Sources

Data Engineer

Business Users

Data Scientist


Governance Officers

Data Steward

CDO

Systems of Insights

Cloud

Hadoop

Social Media

Unstructured

Other External

IOT

Systems of Record

Users

Logs


Data Lineage *







Mgt *







Data Replication *




Knowledge

Catalog












Data Sources

Data Engineer

Business Users

Data Scientist


Governance Officers

Data Steward

CDO

Systems of Insights

Cloud

Hadoop

Social Media

Unstructured

Other External

IOT

Systems of Record

Users

Logs











Data Replication *



Knowledge

Catalog









Entity & Consent Management *Data Lineage *



**




Data Architect Data Engineer Data Steward Knowledge Worker

IBM Information Governance Catalog IBM Watson Knowledge Catalog

IBMs Data Catalog Product Direction 2019

Persona Specific Experiences

Embeddable Catalog Micro-Services

Open MetadataOne Scalable CatalogAvailable Multi-Cloud

21

People Culture Data

To be successful with AI,

you need the right approach

IBM AI enabling technologiesIBM Cloud / © 2019 IBM Corporation

22

More Information

https://www.ibm.com/analytics/cloud-pak-for-datahttps://www.ibm.com/analytics/

Thank you

https://www.ibm.com/analytics/cloud-pak-for-data

https://www.ibm.com/analytics/

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Data and AI be ready for AI with trusted data€¦ · Marketing/Ad budget optimization Loyalty program analytics Shop geolocation optimization Logistics optimization Digital Experience